william-(will)-cross,-ph.d

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Engineering, Done DIRT Cheap: How an Outdated Data Architecture Becomes a Tax on Innovation

In March 2021, I wrote about The Innovation Tax : the idea that clunky processes and outdated technologies make it harder for engineering teams to produce excellent tech that delights customers. In the months since then, my thinking has evolved even further. I couldn’t have guessed how many technology leaders would immediately recognize these problems in their own organizations and share their own deep frustrations with me. This article puts that evolved thought together with the massive feedback that piece received. It will give you actionable ways to decrease your tax burden — and who wouldn’t want that? The innovation tax, like income tax, is real. Of course, it saps morale (with resulting attrition and churn), but it also has other financial and opportunity costs. Taxed organizations see their pace of innovation suffer as people and resources are locked into maintaining rather than innovating. We named this tax DIRT . Why? Well, it’s rooted in data (D), because it so often springs from the difficulty of using legacy databases to support modern applications that require access to real-time data to create rich user experiences. It affects innovation (I), because your teams have little time to innovate if they’re constantly trying to figure out how to support a complex and rickety architecture. It’s recurring (R), because it’s not as if you pay the tax (T) once and get it over with. Quite the opposite. DIRT makes each new project ever more difficult because it introduces so many components, frameworks, and protocols that need to be managed by different teams of people. In retrospect, it’s clear that technology leaders would recognize this tax and immediately grasp the degree to which it’s caused -- or cured -- by their data architecture. Data is sticky, strategic, heavy, intricate -- and the core of the modern digital company. Modern applications have much more sophisticated data requirements than the applications we were building only 10 years ago. Obviously, there is more data, but it’s more complicated than that: Companies are expected to react more quickly and more cleverly to all of the signals in that data. Legacy technologies, including single-model rigid, inefficient, and hard-to-program relational databases, just don’t cut it. In over 300 CxO conversations I've had since joining MongoDB in 2020, fewer than a handful of CTOs disputed this statement. When your tech stack can’t handle the demands of new applications, engineering teams will often bolt on single-purpose niche databases to do the job (think time series, text, graph, etc.). Then they’ll build a series of pipelines to move data back and forth. And everything will get slow and complicated — and even political. Time to polish up that LinkedIn profile. If this were rare, it wouldn’t be such a big deal. But large enterprises can have hundreds or thousands of applications, each with their own sources of data and their own pipelines. Over time, as data stores and pipelines multiply, an organization’s data architecture starts to look like a plate of spaghetti. Soon you’re operating and maintaining an entire middleware layer of ETL, ELT, and streaming. The variety of technologies, each with their own frameworks, protocols, and sometimes languages, makes it harder for developers to collaborate. It makes it extremely difficult to scale, because every architecture is bespoke and brittle. Developers spend their precious “flow” hours doing integration work instead of building new applications and features that the business needs and customers will love. Enterprise architects often end up spending their time on all the wrong things. It’s clear to me that most customers are ready for a new approach to data architecture. One of the best parts of my job is listening to and learning from other CxOs. Since the pandemic made it impossible to do that in person, MongoDB moved these discussions online, inviting technology leaders to hash out some of their biggest problems 1:1 and in groups with me. In one of those sessions, a CTO commented, “Technical debt should be carried on your CFO's balance sheet.” Even on Zoom, the power of that statement was clear. We also started looking at slide decks about data architecture from some of the best-known venture capital firms. Certainly VCs must position each of their portfolio companies as a critical player in the data architecture of the future. But the overall vision was not compelling. One technology leader said, “When I look at 20 net-new technologies I need to learn, it’s terrifying.” Others commented that just looking at these architecture diagrams was a little off-putting, because they knew their own organization’s data architecture was at least that complicated already. They knew they needed to simplify their data architecture, but more than one admitted to postponing this work -- indefinitely -- because it was just too daunting. I recently met with a major health care company whose executives think it’s just barely possible, but they are bravely diving in anyway, knowing that they must do it and that they’ll learn along the way as they tear down their monoliths. In many cases, the innovation tax manifests as the inability to even consider new technology because the underlying architecture is too complex and difficult to maintain, much less understand and transform. This is why a lot of senior people at enterprise companies are sitting with their fingers in the transformation dike, waiting for retirement -- they think they can’t modernize. It won’t surprise you that we also saw how MongoDB, as a general purpose database able to handle all types of data at speed and scale, could help solve this problem. Let me be clear. I’ve been working on or with databases for my entire 35-year career, and I joined MongoDB for a reason: I believe we can build the database and application-building environment that I’ve wanted to create and use for at least 30 of those years. Our vision of MongoDB goes beyond our namesake database to a broader, more versatile application data platform that allows you to accelerate and simplify how you build any type of application. It represents significant progress toward our larger goal, which remains the same as ever: to make data stunningly easy to work with. We want to see data become an enabler of innovation, not a blocker. And we want to finally allow technology teams to start to untangle their sprawl and get rid of their DIRT. Where to start? It’s good to have a better understanding of just how DIRT might be holding your teams back. Do your developers have trouble collaborating because the development environment is so fragmented? Do schema changes take longer to roll out than the application changes they’re designed to support? Do you have trouble building 360-degree views of your customers? And if so, why? These are all good places to start digging in the DIRT. You might also take a hard look at your applications and data sources, as well as what it would take to move your data onto an application data platform. That could mean identifying the objects in your applications and all the applications that interact with them. You could then assign a complexity score to each one based on attributes such as properties, methods, collections, and attributes. Now take a step back and identify each application that connects to each of those objects and rank it based on how mission-critical it is, how many people rely on it, how many tasks it has to perform, and the complexity of those tasks. Once you have a better handle on all this complexity, you’ll be better positioned to create a plan to move off your legacy systems, perhaps starting with the least complex and least integrated data sources. Of course, your metrics and your mileage will vary, but the point is to start. I don’t pretend any of this is easy. Like many of you, I’ve spent most of my career working on problems just like these. But that also means I know progress when I see it, and the beginning of a way for organizations to start to clean up their DIRT. I’ll be continuing to write more about these challenges and hopefully continue to add some perspective. If you’re curious to learn more about DIRT, you can download our white paper . As always, I’m eager to have you tweet your alignment, lack thereof, or other thoughts at @MarkLovesTech . You can also reach out to me on marklovestech.com , where you will find a compilation of my latest musings related to MongoDB and otherwise.

November 24, 2021

The Power of Embracing Differences: My Journey to MongoDB

September 14th, 2021 marked my first full year at MongoDB, and what a year it’s been. A bit about me Hi, I’m Cara! I’m a Team Lead, Executive Assistant, specifically for Tech & Product. I’m based out of our NYC office and live in Jersey City with my girlfriend and our three cats. At MongoDB, I support our amazing Chief Product Officer and also lead a team of awesome Administrative Assistants (AAs) and Executive Assistants (EAs) within Tech & Product. We are hiring like crazy, too, and I can’t say enough great things about our team. Beyond my already rewarding and challenging role as a Team Lead, I also get to work on other meaningful projects while growing my core career. I’m incredibly grateful and humbled to be a Global Lead for two of MongoDB’s affinity groups (known as employee resource groups at some companies) alongside some of the best, most passionate people I’ve ever met: Queeries - A closed group and safe space for people who personally identify within the LGBTQIA+ spectrum. The Queer Collective - An open group for the LGBTQIA+ community as well as our amazing allies (all are welcome!) to exchange thoughts, ideas, and learn and grow from each other. As we like to say, the future is inclusive! Finding my voice and professional purpose The funny thing is, I didn’t know what an “affinity group” or “employee resource group” was for most of my career. I used to work in a more conservative corporate environment and spent over a decade in the food/hospitality industry with people whose views were wildly different from mine. One of my bosses always asked me if I had a boyfriend or when I was going to settle down with a nice guy. It was awkward and uncomfortable, but it was a discomfort I got used to. How sad is that? The crazy thing was, it didn’t feel sad or weird or anything at the time. I just thought I had to stay hidden at work. That’s what you did. It wasn’t “professional” to be gay. The first time I saw a queer coworker was when I had my first real introduction to the tech start-up environment. He was so vibrantly open about who he was, and I was in awe of him. I stayed quiet for my first few months there and studied people’s reactions, interactions, and how they responded when he would say things that I never thought could be said in an office. They weren’t bad things by any means, but they were topics about being queer that I watched everyone embrace. Then, it slipped out during lunch one day. I thought maybe I could casually mention going on a date so it would be less weird, but everyone was super surprised. I get told I “look straight” a lot, which I’ve always found irritating. What does that even mean? Do I need to be masculine-presenting to be gay? Me (right) and my girlfriend From there, I moved on to work at Zocdoc, which truly opened my eyes to affinity groups, workplace queer communities, and how far they expand. It was the first place I worked that even had an affinity group. I befriended two amazing humans there who were the founders of ZocPride, which represented Zocdoc’s queer community. We got to talking and they told me they only planned something for Pride month. They’re not planners, they actually hate planning, but they didn’t want the group to die. So I said, “Good news. Hi, I’m Cara. I’m super queer and I love to plan things!” We chuckled and then I immediately started planning and researching what I could do with this awesome gift I was just given. Since we had no D&I team and a very limited budget, I worked to find other companies to partner with as well as vendors who would be open to sponsoring events for us. Before I knew it, we were partnering with Out in Tech to host an external panel discussion about queer access to healthcare. We hosted it on Coming Out Day and had about 300 guests. From there, things really took off. We did a “spread the love” campaign for Valentine’s Day, had hugely successful fundraisers for NYC’s AIDS Walk, and then, you guessed it, went crazy for Pride. I proudly introduced the art of drag to Zocdoc and started their annual Drag Bingo Pride event. We also sponsored and had a booth at the Lesbians Who Tech Summit the year that Hilary Clinton came to speak. It was unbelievable. My MongoDB journey After receiving incredible offers to work at a few more companies, unexpectedly experiencing workplace discrimination, and reflecting on what I want and need to be happy and thrive in a work environment, I found myself at MongoDB. One of my amazing colleagues from Zocdoc was working here and we were catching up. I heard the details about the Company and role and thought it sounded like a great fit! I love working in tech, but specifically with Product & Tech teams. They’re brilliant, passionate, quirky personalities that vibe well with mine and in my experience, are hyper-focused on having fun and building a positive culture. Because of my previous experiences, I knew exactly what I was looking for. I asked questions that could be uncomfortable to some, as far as the company’s commitment to Diversity & Inclusion, what it means to them personally, and how they practice what they preach. I didn’t want any more wooden nickels. The interview process was amazing. Everyone was super responsive, informative, and helpful and didn’t hesitate to answer any of my hard-hitting questions. Interviews are a two-way street, and I was immediately put at ease when I realized that MongoDB was the place for me. My recruiter started telling me about our growing D&I team, our affinity groups, and how involved and supportive the leadership team is. Then I got to interview with my manager, our Chief Product Officer, who I clicked with instantly. I knew right away that I wanted to work with him. In my experience, I haven't always been lucky with great bosses. I’ve been ignored, lied to, dismissed, looked over, and simply not appreciated. I don’t feel that way here. I feel heard and respected, and that speaks volumes in itself. I’m often encouraged to take time for myself. I had some personal health issues at the beginning of the year. I was anxious to take time off because I was still so new, but the outpour of support and understanding I received blew my mind. That’s when I knew I had really found my new home. When I joined MongoDB last year, The Queer Collective was still a new group, only three months old at that point, and I was able to join at a very exciting time when there was lots of opportunity and momentum. We officially launched the group alongside the communication of launching our first-ever celebration of (inter)national Coming Out Day . We celebrated again this year and have decided that it will be a company-wide annual tradition. Last year, four of our leads (myself included) shared their coming out stories, and we didn’t realize how much of an impact it made until feedback started to trickle in. We were told that some employees joined MongoDB after reading our stories and some even felt comfortable coming out of the closet and stepping into their own light. If that’s not rewarding, I don’t know what is. This year, more employees shared their stories , and we partnered with our Benefits team to host an internal panel discussion. October is Mental Health Awareness Month, and we thought it would be the perfect time to talk through and bring awareness to the mental health journey that comes along with coming out and embracing your true, authentic self. We will also be planning a full week of impactful programming for Trans Awareness Week so that we can continue to amplify the voices in the Trans Community while encouraging continued education. This past July, I also spoke at MongoDB.live (formerly known as MongoDB World) with my Queer Collective co-lead and dear friend Seán Carroll about Allyship and how to upgrade to an active accomplice. It explored what accountability and support look like and how we can all improve our support of the LGBTQIA+ community. The feedback was amazing, and I can’t wait to evolve our topic and content and hopefully speak in person next year! I also have the pleasure of working closely with our incredible D&I team on impactful initiatives, such as helping with large external events and partnerships like the Lesbians Who Tech Summit, where we secured a top-tier sponsorship at the largest queer tech event in the world! I’ve also been part of meaningful conversations, such as expanding gender and identity options and helping to evolve and plan for benefits that help and impact the Queer community. The list goes on, really. I frequently sync with our D&I team and I’m so grateful to work somewhere that truly invests in fostering an inclusive and equitable work environment. Why MongoDB is the place for me I’ve worked in a lot of different industries, with people from every level and walk of life, and now I feel as though I’m where I was meant to be. MongoDB’s values truly align with my own, and this is the first company that I’ve seen make an actual effort to align their company objectives and goals with their values. Here’s how I live some of our MongoDB values every day: I proudly embrace the power of everyone’s differences (mine included). We evolve and move forward with a magical combination of varied backgrounds, interests, and ideas. Why bother doing anything if you don’t plan to make it matter ? I stand behind everything I work on and am proud of the meaningful projects and impacts I’ve seen first-hand so far. I’ve always been a big idea kind of human - Think Big, Go Far - I thrive on creativity, ambition, and being a relentless dreamer. When I joined, I received a postcard from our CEO. Part of it said, “We want your time here to become a real inflection point in your professional career”, and I can wholeheartedly say after just my first year, it already is. I’m constantly learning and growing at MongoDB. From management training to webinars to endless learning and development resources, and beyond. These were things I had been requesting, asking, and looking for at previous companies. They were things promised to me “eventually”, but they never came. Here I was in my first week at MongoDB, given them without asking. This is a company that truly cares about its employees’ development and success. I’ve hired (and am growing) an awesome team of amazing humans who I’m so proud to work alongside every day. Any job can be great, but the people make it extra special. The EA team at MongoDB is like no other, and I can’t wait to see its continued growth and evolution. Helping to build and evolve a world-class EA org is incredibly exciting and rewarding, and I love being a part of it. I love that I can be fully myself at work and am given the opportunity to make an impact in so many ways. I can’t wait to see what the future will bring. It’s been an unbelievable experience and journey so far! Interested in joining MongoDB? We have several open roles on our teams across the globe and would love for you to transform your career with us!

November 23, 2021

Five Tips for Writing Your Marketing Resume

We are always looking for talented and passionate marketers to join our team at MongoDB, and we want to set you up for success starting at the first step in our recruiting process. No matter how many positions you’ve applied for in the past, it’s always a good idea to refresh your resume for each application. If you’re interested in applying to our Marketing team, take a look at my tips for writing an impactful resume. Length and formatting There are some resume formatting tips that you may already know, but I think it’s great to start with the basics. I recommend keeping your resume to two pages or less and breaking it into sub-sections. The top of your resume should have your name, contact details (phone number and email address), and a link to your LinkedIn profile. Next, I recommend including a short summary of you and your experience. For marketing roles, it’s always great to get some insight into the companies and teams you have worked with, projects you have taken part in or led, and some of the main skills you feel you could bring to MongoDB. Next should be your experience. I always advise candidates to break their experience section into three different parts: Company and role: Provide a brief description of the company you previously worked at and a high-level overview of your role there. Responsibilities: Utilize bullet points to provide more detail about the main responsibilities you held while working there. Highlights and achievements: I recommend showcasing some of the main achievements you have had while working in each role. This helps provide a clear picture of your skills and capabilities. At the bottom of your resume, list your highest level of education achieved and any degrees you hold. You may also consider including additional information such as charity or volunteer work you’ve done, other activities you participate in, or hobbies and interests. While we are interested in your professional experience, we’re also interested in learning about you as a person! Highlights and achievements During the recruiting process at MongoDB, we want to learn as much as we can about you. Your resume is your chance to highlight all the great things you’ve done in your career. To reiterate the above, I recommend adding a section under each role you’ve held to list some of your top achievements. This will help show us where your strengths are and how you could impact the Marketing organization at MongoDB. Achievements could be marketing events you held and the impact they had on the organization or campaigns you ran that had a great return on investment. Any internal awards or recognitions you received would be great to add here, too. Numbers, stats, tools, and links As you are listing your highlights and achievements, I’d like to mention that adding numbers and statistics can really go a long way in making your resume stand out. For example, maybe you ran a campaign that led to an uptick in sales leads and conversions. Consider providing the data to showcase this. Visual aids like charts and graphs are also a great addition. If you have some examples of campaigns, webpages, or events you’ve managed, consider adding links to them within your resume. Resumes that are both qualitative and quantitative have the greatest impact and are quickly noticed. Listing some of the marketing tools you have used is also helpful for the recruiter and hiring manager to understand your experience with marketing technology. Under each role, I’d recommend adding a list of the tools you used and your proficiency with them. At MongoDB we use tools such as Salesforce, Tableau, Eliqua, and Splash, so if you’ve had experience with any of those, be sure to highlight it! People management If you are applying for a people management role, I recommend highlighting the mentoring and coaching experience you gained through your management experience. It is also helpful for potential hiring managers to understand how many direct reports you had in previous roles and the seniority level of these direct reports. Attention to detail As a recruiter, I've seen spelling and grammar mistakes on resumes at all levels and from all sectors. We are only human at the end of the day, but when applying for roles in areas such as marketing where attention to detail is key to success, it’s best to give your resume a second (or even third) look. Ensuring that your resume is well-written, grammatically correct, and formatted in an easily readable way will really make it stand out. I hope to see your resume in our applicant tracking system soon! Interested in pursuing a career in marketing at MongoDB? We have several open roles on our teams across the globe and would love for you to transform your career with us!

November 18, 2021

Introducing the MongoDB Atlas Data API, Now Available in Preview

As the leading application data platform , we’re hyper-focused on accelerating and simplifying how developers leverage their application data. This has led to the introduction of features like serverless instances and the Atlas Triggers that minimize the operational burden associated with traditional database workloads. Today, we’re excited to announce the next step forward in this mission with the introduction of the MongoDB Atlas Data API – a fully managed, REST-like API for accessing your Atlas data. The Data API makes it easy to perform CRUD and aggregations on your data in minutes and allows you to query MongoDB from your backend in any language, without the need for drivers. The next level of data access Organizations are increasingly relying on operational data layers to build distributed architectures like microservices for their modern applications to speed-up development and stay competitive in rapidly changing markets. These stacks often require scalable, highly available, and secure access to the data layer. The most popular way to architect these data services is to build APIs that communicate with MongoDB data over HTTPS using REST or similar protocols. However, creating a custom-built API typically takes a lot of time and effort. It's a painful process that introduces unnecessary operational burdens like provisioning additional servers, connection management, and scaling. With the Atlas Data API, customers can generate a fully managed, REST-like API for their Atlas data in seconds. Developers no longer need to worry about the underlying infrastructuring of their APIs, and instead can enjoy the efficiency of intuitive, out-of-the box data access, while still being able to leverage the always-on and highly available qualities of Atlas as the underlying database. This unlocks a whole new level of developer productivity for use cases that were previously time consuming to accomplish – such as building data-centric microservices, simplifying access from serverless functions, and integrating with third party services . The API even has built-in support for aggregation pipelines to use with services like Atlas Search . Try the Atlas Data API All customers now have the ability to enable the Data API for their Atlas deployment. We invite you to try it out today with a new or existing Atlas account. It’s incredibly easy to get started: simply choose the cluster you’d like to connect to and generate an API key. That’s all it takes to set up and start accessing Atlas data. Have questions? Check out our documentation or head over to our community forums to get answers from fellow developers. What's next for the Atlas Data API This preview release is just the beginning. Support for services like Data Lake and Serverless Instances will be added over the coming months. And, long term, we see the Data API as the next step in our journey to abstract and automate infrastructure decisions – to help developers build the future faster. Atlas Data API documentation can be found here

November 18, 2021

Simplifying Compliance with VComply & MongoDB

As businesses globally are facing external pressures to be more focused on privacy, security, and transparency, compliance management is needed now more than ever. With 200+ regulatory updates, 900 regulatory agencies, and the average cost of a non-compliance incident being $14 million, maintaining compliance is critical for every business, no matter the size. Tracking, maintaining, and proving compliance has traditionally been incredibly difficult, resource-intensive, and takes a significant time commitment. That's why one startup aims to simplify compliance by disrupting the antiquated industry. Enter VComply . Founded in 2019, VComply is a governance, risk management, and compliance (GRC) platform that enables its customers with a secure and easy-to-use solution. VComply is highly configurable to meet the specific needs of any organization without additional coding or infrastructure changes. The platform collects, organizes, analyzes, and automatically reports on GRC data inputted into the system to provide a high-level view of an organization's compliance posture at any given time. Combining that with the ability to surface detailed information on any control, VComply modernizes how people work and interact with GRC programs within their businesses. In this week's #BuiltWithMongoDB, we take a look at VComply to learn more about how they are truly helping organizations strengthen their risk and compliance management. We spoke with Harshvardhan Kariwala, CEO, and Ashish Jha, Vice President of Engineering at VComply to discuss the company's journey and how they decided to build with MongoDB. What inspired you to build the business? Harshvardhan: VComply is actually my third startup. At one of my previous companies, I had become hyper-focused on building the business, and I eventually lost sight of compliance. Operational functions fell through the cracks, and I ended up outsourcing our compliance programs to this corporate firm in Singapore. Fast forward a bit, they ended up forgetting to do a required compliance filing, and we ended up responsible for paying the non-compliance fines associated with that. One reporting misstep, and we were fined. That's what got me worried. We got lucky that was all that happened. It only took one time to inspire action. We then built an internal tool where the entire idea was around creating a culture of reporting excellence and internal accountability. After adopting our newly created tool, in 2018, we realized that we built a very robust solution to real day-to-day compliance problems. We thought, "Why don't we spin this off into its own product?" By that time, I was ready to get back into product development, and this was the perfect opportunity. In early 2019 we set up VComply. We quickly got our first customer, the City of Boston, and never looked back. So that's where VComply got its start. It was never meant to be sold as a product. It was more of an internal compliance tracking tool. That's how we entered the GRC space. What exactly does VComply do? What are some of its most useful product features? Harshvardhan: We help businesses be compliant, mitigate risk, and adopt a culture of transparency. If there isn't internal alignment within a company, no tool is going to help them. At its core, VComply is designed to be easy to use so that anyone in an organization can adopt a compliance-first mindset. By removing the traditional technological barriers, we found that businesses can realize the benefits quickly. That said, VComply serves as the single source of truth for everything GRC within an organization. Think tracking compliance obligations, compliance monitoring, automating activities, alerts and follow-ups, compliance evidence collection, audit trails, and more. Another popular piece of our tool is our enterprise risk management as well as policy management functionalities. You can monitor and manage risk programs, quickly identify risks, and start linking compliance obligations to mitigate that risk. What makes VComply stand out from its competitors? Harshvardhan: Most other solutions on the market require a compliance expert, are hard to navigate, and take a significant time commitment upfront to get up and running. We built VComply to be more practical and realistic with how people manage their compliance and risk programs today. VComply is easy to set up, simple to use for the end-user, and flexible to map to the specific controls a business needs to comply with without any additional coding. How did you decide to build with MongoDB? Ashish: Easy and intuitive search support, as well as indexing and automated performance suggestions, were the key drivers for us building with MongoDB. Also, training new developers is very straightforward. What has your experience been like scaling with MongoDB? Ashish: Scaling is pretty seamless with MongoDB. Setting up alerts and monitoring is very straightforward. We've had nothing but great experiences so far. Do you have a favorite technical book or podcast that you would recommend to other tech entrepreneurs? Harshvardhan: I would recommend The Great CEO Within: The Tactical Guide to Company Building by Matt Mochary. That's definitely a great read. This is a bit of an open questions, so feel free to interpret it how you'd like. What are you currently learning? Harshvardhan: That's a tough one. I think you're always learning so many different things on any given day that it's difficult to give one answer. Today, I'm learning marketing strategies, like demand gen as well as sales tactics to scale the business. Ashish: Primarily, I'm learning how engineering can augment and support other organizations within the company. Who are some tech leaders or entrepreneurs that you admire? Ashish: I do admire Jeff Bezos quite a bit. I admire the laser focus that he has and the clarity in terms of his reasoning. Harshvardhan: Elon Musk because of his ideas and execution. One thing that's great about him is how he executes his ideas flawlessly. Interested in learning more about MongoDB for Startups? Learn more about us here .

November 17, 2021

Preparing for Your Consulting Engineer Interview at MongoDB

Are you a software professional who isn't always just about the software? Do you write code, but just as often get an equally strong sense of accomplishment by configuring a tricky but vital part of the operating system or DBMS? Do you enjoy working with a variety of computer professionals from SysAdmins to Devs to CTOs? Do you feel that special spark from knowing there's so much more to learn about the technology you eat, sleep, and breathe, and that you might never learn every last bit of it, but it'll be a heck of a ride trying to? Are data management and consulting two things you enjoy doing more than anything else? We are always on the lookout for such professionals. Those who seek the challenge. Those who can immerse themselves in every cubic millimeter of a particular stack in their quest to find “the answer”. Those who find fulfillment in helping MongoDB's customers realize every bit of potential that our products can give them. MongoDB Professional Services provides best-of-breed expertise and experience for all of our products to help our customers and community users get the most out of them. This can involve one or more of: Application Lifecycle Expertise, providing both strategic and tactical consulting from the conception to delivery to post-delivery phases of your application lifecycle Dedicated time with a dedicated MongoDB technical expert, with all of the resources of the company and the community at their disposal Public and Private Training for DBAs, DevOps Engineers, Developers, and Data Scientists Migrating customer workloads to MongoDB in Public Clouds And on the front lines is the Consulting Engineer (CE). The Jack-of-all-trades of all things MongoDB who works directly with our customers on a daily basis. What follows is a guide for those looking to join MongoDB Professional Services. We have Consulting Engineer positions available at a variety of levels, and this guidance should help make for the best possible interview experience! Do you have what we're looking for? Contrary to popular belief, you do not need to know how to use MongoDB. Trust me, that was my situation when I interviewed with MongoDB. Don't get us wrong, it is a definite “plus” to have some experience or be an expert, but no experience with MongoDB isn't a deal-breaker. It also isn't an absolute requirement to have been a Consulting Engineer before (I hadn't been), but you do need the skills and qualities that can be made into a successful CE. We look for bright, motivated people who can learn quickly, pivot effortlessly, and adapt relentlessly to a myriad of challenges and situations. People who rise up to technical challenges in pursuit of our customers' needs. We are mostly focused on customers after the sale, although we do work in tandem at times with our Account Teams. A MongoDB Consulting Engineer is well-versed in modern software stacks, database technologies, software development, deployment, and day-to-day operations. They utilize MongoDB Best Practices, deliver MongoDB Technical Training, and work with both customer Dev and Ops teams to ensure successful deployments of MongoDB-based software solutions. They are resourceful, adaptable, always willing to learn, and (if and when we get back to it) comfortable travelling a majority of the time. They enjoy interacting with software professionals on a daily basis. They enjoy representing MongoDB and its products and technologies. They enjoy real-world technical challenges. Do we have what you're looking for? The very first step in your journey is to check the Customer Engineering careers page for open Consulting Engineer positions. If one or more look like a potential fit, we encourage you to apply! As an organization, MongoDB Professional Services strives to be one of the best in the industry. We adhere to very high standards, which translates to maximum benefit to our customers. We are always learning from each other and learning about our new products and technologies as they come down the pipeline. We work hard, we have a lot of fun, and we make a difference. Because a Consulting Engineer must possess a broad skill set, there is significant potential for career growth within the organization. People management is one route, or you might decide you'll always prefer to 'stay technical' - in the latter case, consider a development path that could land you a coveted MongoDB Distinguished Engineer position some day. Alternatively, you might at some point determine that you wish to move into other Professional Services roles with other emphases, such as: Tool and Framework Development for our customers, as well as your fellow Consulting Engineers Curriculum Development, for internal or external Training offerings Engagement Management, where you working more closely with Account Teams to present Professional Services' value proposition to potential and current customers Project Management You are given extensive freedom as a MongoDB Consulting Engineer. We give you the freedom to explore, the freedom to create, the freedom to learn, and the freedom to contribute to the organization and our customers in your unique way. Do you aspire to give a presentation at a MongoDB.local or at MongoDB World? Perhaps the written word is your thing, and you'd like to try your hand at blogging for MongoDB and Professional Services (like I'm doing right here!). Or maybe you just like to develop new and interesting tools for other MongoDB users through the MongoDB Community. All of those and more are possible. Is that what you're looking for? As a company, MongoDB aims to be recognized as a leader in how we value and look after our employees, as well as our customers. Want to learn more? Check out our Life At MongoDB blog posts. Interview step one: speaking with a recruiter Once you've applied for a Consulting Engineer position, a Recruiter will review your resume and determine if they think your skills and experience could be a good fit for the role. If so, they’ll reach out to you to get to know you better and to discuss your qualifications for the particular position, your experience in the industry to date, and what you are looking for in a position with MongoDB. The more you can reflect on your experience and expertise and then show its applicability to what we're looking for, the better. Think about what you are wanting in a career at MongoDB as a Consulting Engineer and how we may be able to make that happen together. A good job fit is, after all, a two-way street. Interview step two: speaking with the hiring manager If the Recruiter confirms that you are a potential fit for Professional Services, you will be scheduled for some time with the Hiring Manager. Give some thought to the following: What do you want out of your next job? What are you looking for in a company and a manager? Why do you feel, at this point, that you are an excellent fit for this position? Pick some example experiences/situations from your past that may be relevant to this position, and be prepared to discuss them. The manager will likely share more about the overall and day-to-day expectations of the job. They will also ask if you have additional questions that they can answer to give you a fuller picture. Our goal is to give you a proper overview of the team (and its culture), Professional Services, and what it's like working at MongoDB. Interview step three: speaking with MongoDB Consulting Engineers In this phase, you will have a handful of one-hour interviews with established MongoDB Consulting Engineers. Each interview covers one or more of the following: Database expertise (Relational and non-Relational) Software development experience and familiarity Problem solving expertise and approach(es) Consulting experience/expertise Rigors of and requirements for daily customer interaction Now: Working with customers remotely (Potentially) In the future: Business travel a majority of the time (note: on hold at present due to COVID) "Soft skills" needed to be a successful MongoDB Consulting Engineer Report writing skills Verbal communication skills (1-on-1 and to groups) Dealing with various customer personalities and situations Comfort talking to customer individual contributors, management, and business stakeholders No, we do not expect you to code an O(n) sorting algorithm on a whiteboard while we wait. Nor do we expect you to install and configure a database server on the fly from a terminal window. That being said, if those sorts of things intrigue you, well…. points for that. What we will do is dig into how you attack problems, how you work with individuals and groups to find solutions, and how you make use of available resources and think outside the box when required. We also ask questions to see how quickly you can absorb new information and how quickly you can adapt to rapidly changing situations. Interview step four: speaking with the PS Director The last stage in the interview process is a chat (usually via video conference) with the Professional Services (PS) Director for that region. This can give you a slightly different perspective of the organization and the role itself, as well as added visibility into our business and company culture. The good news is that this will not be as technical as the interviews above. Before this discussion, consider what you've discussed so far in the interview process, and what other aspects of the role you have further questions about. I will say that when I interviewed back in the day, I sat down with our newly-hired head of Professional Services and asked him "where do you see the organization in two to three years?". His answer was a significant piece of why I accepted MongoDB's offer, so don't be afraid to ask what's really on your mind! Questions? I love to make connections between outstanding individual contributors and MongoDB Professional Services, so if you have any questions about this process or the jobs, feel free to drop me a line. If you’d like to hear more about my experience as a Principal Consulting Engineer, listen to this episode of The MongoDB Podcast. You can find me on LinkedIn, or by writing to me at eric.reid@mongodb.com . Good luck! Interested in pursuing a career as a Consulting Engineer at MongoDB? We have several open roles on our teams across the globe and would love for you to transform your career with us!

November 16, 2021

Announcing Google Private Service Connect (PSC) Integration for MongoDB Atlas

We’re excited to announce the general availability of Google Cloud Private Service Connect (PSC) as a new network access management option in MongoDB Atlas . Announced alongside the availability of MongoDB 5.1 , Google Cloud PSC is GA for use with Altas. See the documentation for instructions on setting up Google Cloud PSC for Atlas, or read on for more information. MongoDB Atlas is secure by default . All dedicated Google Cloud clusters on Atlas are deployed in their own VPC. To set up network security controls, Atlas customers already have the options of an IP Access List and VPC Peering . The IP Access List in Atlas is a straightforward and secure connection mechanism, and all traffic is encrypted with end-to-end TLS. But you must be able to provide static public IPs for your application servers to connect to Atlas, and to list those IPs in the Access List. If your applications don’t have static public IPs or if you have strict requirements on outbound database access via public IPs, this won’t work for you. The existing solution to this is VPC Peering, which allows you to configure a secure peering connection between your Atlas cluster’s VPC and your own Google Cloud VPC(s). This is easy, but the connections are two way. Atlas never has to initiate connections to your environment, but some Atlas users don’t want to use VPC peering because it extends the perceived network trust boundary. Access Control Lists (ACLs) and IAM Groups can control this access, but they require additional configuration. MongoDB Atlas and Google Cloud PSC Now, you can use Google Cloud Private Service Connect to connect a VPC to MongoDB Atlas. Private Service Connect allows you to create private and secure connections from your Google Cloud networks to MongoDB Atlas. It creates service endpoints in your VPCs that provide private connectivity and policy enforcement, allowing you to easily control network security in one place. This brings two major advantages: Unidirectional: connections via PSC use a private IP within the customer’s VPC, and are unidirectional. Atlas cannot initiate connections back to the customer's VPC. This means that there is no extension of the perceived network trust boundary. Transitive: connections to the PSC private IPs within the customer’s VPC can come transitively from an on-prem data center connected to the PSC-enabled VPC with Cloud VPN . Customers can connect directly from their on-prem data centers to Atlas without using public IP Access Lists. Google Cloud Private Service Connect offers a one-way network peering service between a Google Cloud VPC and a MongoDB Atlas VPC Meeting security requirements with Atlas on Google Cloud Google Cloud PSC adds to the security capabilities that are already available in MongoDB Atlas, like Client Side Field-Level Encryption , database auditing , BYO key encryption with Google Cloud KMS integration , federated identity , and more. MongoDB Atlas undergoes independent verification of security and compliance controls , so you can be confident in using Atlas on Google Cloud for your most critical workloads. To learn more about configuring Google PSC with MongoDB Atlas, visit our docs . If you’re already managing your Atlas clusters with our API, you can add a private endpoint with the documentation here . For more information about Google Cloud Private Service Connect, visit the Google Cloud docs or read the Introducing Private Service Connect release announcement. Try MongoDB Atlas for free today!

November 11, 2021

Turning MongoDB into a Predictive Database

There’s a growing interest in artificial intelligence (AI) and machine learning (ML) in the business world. The predictive capabilities of ML/AI enable rapid insights from patterns detected at rates faster than manual analysis. Businesses realize that this can lead to increased profits, reduced costs, and accelerated innovation. Although businesses both large and small can benefit from the power of AI, implementing a predictive analytics project can be both complex and time-consuming. MongoDB , Inc. (NASDAQ: MDB), the leading, modern general purpose database platform, and MindsDB , the open-source machine learning platform that brings automated machine learning to the database, established a technology partnership to advance machine learning innovation. This collaboration aims to enhance the ability to streamline predictive capabilities for data science and data engineering teams within organizations to solve real-world business challenges. What is the best approach? Once you have identified the initial ML projects you’d like to focus on, choosing the right tools and methodologies can help speed up the time it takes to build, train, and optimize models. Model selection and feature engineering can be time consuming and difficult if you aren’t aware of the specific dimensions the ML model is going to train on. AutoML models excel at testing a wide variety of different algorithms to model a hypothesis of interest. Existing state-of-the-art AutoML frameworks provide methods to optimize performance including adjusting hyper parameters (such as the learning rate or batch size). The MindsDB AutoML framework extends beyond most conventional automated systems of hyper parameter tuning and enables novel upstream automation of data cleaning, data pre-processing, and feature engineering. To empower users with transparent development, the framework encompasses explainability tools, enables processing for complex data types (NLP, time series, language modeling, and anomaly detection), and gives users customizability by allowing imported models of their choice. MindsDB also generates predictions at the data layer—an additional, significant advancement that accelerates development speed. Generating predictions directly in MongoDB Atlas with MindsDB AI Tables gives you the ability to consume predictions as regular data, query these predictions, and accelerate development speed by simplifying deployment work-flows. Getting started with MindsDB We suggest starting with http://cloud.mindsdb.com for a cloud managed version of MindsDB . MindsDB is an open source project (http://github.com/mindsdb/mindsdb), so you can alternatively install it on your machine and run it locally. For simplicity, we recommend the docker installation described below: Install MindsDB using Docker First, check that you have docker installed by running: docker run hello-world To pull the image, run the following command: docker pull mindsdb/mindsdb Then, run the command below to start the container: docker run -p 47334:47334 -p 47336:47336 mindsdb/mindsdb If docker is not an option, you can follow our docs on how to install MindsDB locally. ( https://docs.mindsdb.com/ ) Setting up the connection Connecting MindsDB to MongoDB can be done in two ways: by using MindsDB Studio (the GUI) or by using Mongo clients (the terminal). Currently, integration works by accessing MongoDB through MindsDB’s MongoDB API as a new data source. More information about connecting to MongoDB can be found here . Use the Mongo shell to connect to MindsDB’s MongoDB API. Please note that you must have Mongo shell version ≥3.6 to use the MindsDB MongoDB API. If you are following this tutorial using MindsDB Cloud you can skip the section about config.json. There is a default configuration setup before starting the MongoDB API. The Mongo host will be the MindsDB Mongo API which is defined inside the host key as 127.0.0.1. Please find below the config.json example. { "api": { "http": { "host": "127.0.0.1", "port": "47334" }, "mysql": {} "mongodb": { "host": "127.0.0.1", "port": "47336", "user": "mindsdb", "password": "", "database": "mindsdb" } }, "config_version": "1.4", "debug": true, "integrations": {}, "storage_dir": "/mindsdb_storage" } The location of the above config.json file can be found in the first output line of the log when MindsDB Server is started as a Configuration file value. If you want to change the host, default username or include password, you can make the changes there. To connect to MindsDBs via GUI: We can use MindsDB Studio to create a connection between MindsDB and MongoDB to access the data we wish to train our model on. Visit http://127.0.0.1:47334/ or http://cloud.mindsdb.com/ from your favorite web browser to access the Studio. From the menu located on the left, select Database Integration. Then, select ADD DATABASE. In the connect to Database window: Select MongoDB as the Supported Database Add the subsequent information as Mongo host, port, username and password Now, we have successfully integrated with the MongoDB database. The next step is to use Mongo-client to connect to MindsDBs Mongo API and train models. To connect to MindsDBs Mongo API for local connection run: mongo --host 127.0.0.1 -u "username" -p "password" If you are using MindsDB cloud, you need to use the username/password to connect to the MindsDB Mongo API. mongo --host mongo.cloud.mindsdb -u "cloud_username" -p "cloud_password" Then use MindsDBs database and list collections: use mindsdb show collections Training a new Machine Learning Model using MQL We will leverage the power of Mongo Query Language (MQL) and MindsDB to train a model. The goal of the model is to predict the strength of a concrete mix, with input columns such as the age, amount of water used, types, and quantities of additives used to make the mix stronger. The dataset can be downloaded from Kaggle and represents a potential business use case in everyday construction projects to optimize the strength of a mix while minimizing the amount of material used—a goal that saves on costs without neglecting function. You can follow this tutorial with your data inside Mongodb or simply just import the csv file in a collection called material_strength. Also, you can get the exported collection from the above data on this URL . To train a new model, we need to call the insert() function on the mindsdb.predictors collection. Notably, the following information must be included: db.predictors.insert({ 'name': 'strength', 'predict': 'concrete_strength', 'connection': 'MongoIntegration', 'select_data_query':{ 'database': 'test_data', 'collection': 'material_strength', 'find': {} } }) The ‘name’ is simply the model name, ‘predict’ is the feature that we aim to predict, and ‘connection’ is the name of the MongoDB connection we have created using MindsDB Studio. Inside the select_data_query we should provide the name of the database, collection and find() function to select the data. Once you enter this information, MindsDB begins the training process. To verify that the training has been completed, you can use the find() command to check the model status inside mindsdb.predictors collection e.g.: Successful training will return a ‘status’: ‘complete’ notification. MindsDB Studio provides additional useful information to go beyond predictions and explain the results. The below figure refers to feature importances, automatically calculated and displayed to reveal which columns of your data likely matter for predictive strength. The following information can be obtained from MindsDB studio by selecting the preview option on your trained model. Moreover, the preview option also provides us with a confusion matrix to help us evaluate the performance of our model by buketizing true and predicted values. As this is a regression task, we stratify the true and predicted values to analyze how effective predictions are at reflecting the underlying data patterns. Strongly performing models have a notable diagonal component: this indicates that a model is successful at detecting the relationship between features and the output distribution. Elements located away from the main diagonal imply less accurate predictions (this could be, for example, due to sparse sampling of data in these output regions). The next step is to use the MQL to get the predictions back from the model collection. Querying the model After we have trained a model, we can go ahead and query the model. Using MQL, we will need to call the find() method on the model collection. In addition, we need to provide specific values for which we would like to obtain a prediction. An example would be: db.strength.find({'age': 28, 'superPlasticizer': 2.5, slag: 1, 'water': 162, 'fineAggregate': 1040}) The model created by MindsDB predicts a value of 17.3 with 90% confidence that the true value lies within the confidence_interval lower and upper bounds. One important piece of information is also the important_missing_information value where MindsDB suggests including values of the cement feature to the find() function will improve the prediction. This tutorial highlights the steps to create a predictive model inside MongoDB by leveraging MindsDB’s AutoML framework. Using the existing compute configuration, the example above took less than five minutes, without the need for extensive tooling, or pipelines in addition to your database. With MindsDB’s predictive capabilities inside MongoDB, developers can now build machine learning models at reduced cost, gain greater insight into model accuracy, and help users make better data-based decisions. Modernize with MongoDB and MindsDB MongoDB provides an intuitive process for data management and exploration by simplifying and enriching data. MindsDB helps turn data into intelligent insights by simplifying modernization into machine learning, AI, and the ongoing spectrum of data science. For a limited time, try MindsDB to connect to MongoDB, train models, and run predictions in the cloud. Simply sign-up here . It’s free (final pricing to be announced later this year), and our team is available on Slack and Github for feedback and support. Check it out and let us know what predictions you come up with.

November 10, 2021

Sales Development Series: Meet the North America Sales Development Team

Sales Development is a crucial part of the Sales organization at MongoDB. Our Sales Development function is broken down into Sales Development Representatives (SDRs), who qualify and validate inbound opportunities from both existing and prospective customers, and Account Development Representatives (ADRs), who support outbound opportunities by planning and executing pipeline generation strategies. Both of these roles offer an excellent path to kickstarting your career in sales at MongoDB. In this blog post, you’ll learn more about our North America inbound team, which works with customers all over North, Central, and South America. Hear from Manager Ravelle Mantoura and a few Sales Development Representatives about the SDR role, team culture, and how they’re looking to grow their careers at MongoDB. Check out the rest of our Sales Development series here . Ravelle Mantoura , Regional Sales Development Manager for North America As part of the inbound Sales Development team, there is an enormous opportunity for growth as you develop many skills in the Sales Development Representative role. Due to the nature of inbound, we tend to have a lot of conversations with customers who are further along their MongoDB journey than others. This means you will have a lot of customers asking questions about the product and features to understand what solution makes the most sense for them. Because of this, you will get well acquainted with the product and develop strong technical know-how around MongoDB offerings. Additionally, you will develop skills to understand how companies of all sizes purchase software. You’ll also have the opportunity to work with dozens of different Account Executives across the company, understand their business flow, their methods, and learn more about their organization -- it’s a great way to build relationships as you decide which path to take. Lastly, due to your customer calls, you will gain a deep understanding of our sales methodology very quickly which will prepare you well for the next role. All of this is incredibly valuable as you look to grow your career and decide which path makes the most sense for you (Enterprise or Corporate). To be on the inbound team means to work alongside marketing closely, understand the marketing to sales funnel, how data impacts results, and how to use the data you are given to have an impactful conversation with a potential customer. You will not be dedicated to one team or region but the entirety of North or Latin America, giving you the opportunity to network, build strong relationships with dozens of different stakeholders, and master your communication and relationship-building skills. We have a few different types of roles on the inbound team, so the typical day-to-day work can vary. For some, a daily structure will be around assisting customers through the live Sales Chat on our website, answering “contact us” forms, or responding to customer calls. This is a fast-paced role where you will help dozens of customers a week who are interested in speaking to sales. We typically schedule a meeting to understand the customer’s project and needs, so a large chunk of your week will be having live video conversations with customers. For the other roles on the team, we have individuals who respond to customers who have engaged with our marketing content. This can be anything from downloading the Enterprise Edition of our database to attending a webinar put on by MongoDB. Reps will reach out via phone, email, and LinkedIn to establish a connection and have a conversation around the potential customer’s interest. Lastly, we just launched a new strategic role on the team where reps will work on Enterprise accounts deemed with a high propensity for growth by marketing. The day-to-day in this role will focus on building connections within the entire account and understanding how the company can potentially leverage MongoDB in their current applications. This role is more strategic so there will be a heavier focus on building out messaging and strategy for approaching the account. The day-to-day in this role will be centered around gathering intel on the account, creating an action plan on outreach, and setting up live conversations with the customers you make contact with. Regardless of what role you’re in on our inbound team, you’ll have weekly, monthly, and quarterly enablement, training, and coaching sessions to set you up for success in your next career step. There are so many things that I love about our inbound Sales Development team. First, I enjoy being able to coach and develop my reps and seeing their growth throughout their tenure as they pursue a sales role at MongoDB. Second, getting the opportunity to learn about companies of all sizes and hear about the cool projects they are working on. Recently, one of my reps had the opportunity to meet with an architect from a popular digital music platform from the ’90s who wanted to completely re-platform their services to capture new market share. Another rep met with the CTO of an AI company where they use robots to track body motion throughout warehouses. Some really cool stuff! Lastly, being part of inbound and handling customers all across North, Central, and South America who are on different parts of the MongoDB journey makes every day exciting! Luiza Ozório , Sales Development Representative When I was looking for new career opportunities, I researched three points that I consider extremely important when assessing the job market: consistent company growth, people and culture, and training and growth possibilities. MongoDB excelled on all these points and when evaluating the two offers I received, I chose to join MongoDB. The Sales Development team culture is very collaborative. We are all on the journey of constant learning, so we often do teach backs on topics that contribute to our daily routines. We also share best practices and anything else that can help other team members develop. There is a culture of learning and development at MongoDB, with well-defined paths for career growth and open feedback which is an exciting working environment to be in. In terms of how to succeed, I don't think there is a specific formula that makes someone successful, but I believe in the importance of being consistent, disciplined, following the sales process, and, above all, communicating with stakeholders in a clear and effective way. Being part of a company that is constantly growing gives us the opportunity to build together and accelerate the company's development even further. I believe in the excellence of what MongoDB offers and I see that we really help our customers develop and scale their businesses. This feeling of being able to help is what energizes me! Brandon Bell , Sr. Sales Development Representative I chose MongoDB because the sales training is second to none. From the first interview, it was clear that MongoDB heavily invests in its people. I felt extremely welcomed and I could tell that MongoDB was a collaborative organization. I spent my first few weeks getting to meet others throughout the organization and going through our Sales Bootcamp which is a training program that’s designed to equip new hires with a strong technology and sales foundation before fully ramping into their role. MongoDB is uniquely positioned in the market to be the foundation for modern applications. It’s an incredible opportunity to be on the ground floor of so many digital transformation efforts. MongoDB is the foundation of so many applications that solve real-world problems! It's incredibly exciting getting to work with various customers with a wide variety of use cases like IoT, Machine Learning, and Blockchain technologies. What will make you successful is being intellectually curious and having a willingness to learn. Our industry and customers' needs are constantly evolving and being genuinely interested in keeping up with these changes is key. At MongoDB, your success is directly correlated with your ability to implement feedback and learn from your mistakes. Coming to the role with an open mind and an appetite to learn is one of the best things you can do as an SDR at MongoDB. My next step is going to be joining our Cloud team as a Cloud Account Executive. In this role, I will get the opportunity to support a lot of early-stage companies as they look to grow and launch new applications. In the long-term, I aspire to become an Enterprise Account Executive where I will get the opportunity to partner with some of the largest companies in the U.S. as they continue to innovate and create applications that will impact millions of people. I feel so fortunate to have joined a sales team that truly cares about everyone's success. Angel Rivera-Vega , Sales Development Representative One of my best friends was working at MongoDB and suggested that I apply to the Sales team based on the continuous growth that he experienced within the company. I had already been developing my tech sales career at other companies, and I knew a little bit about MongoDB through NodeJS and Javascript courses that I took back in 2017. I applied, and here I am! My onboarding experience with MongoDB was gold. I was blessed with a team that consistently helped me through the onboarding process. They always supported me when I needed it, and they consistently coached me on the path to success here in MongoDB. I have to admit that my journey through MongoDB’s Sales Bootcamp was the best sales training process in my professional career. Something that makes me feel very excited about my role is that I have the opportunity to help multiple entrepreneurial initiatives become a reality. I also enjoy promoting solutions to challenges that help enterprises in the long run. It feels great to interact with different companies across the globe and learn about different cultures. In my opinion, there are two critical elements for an SDR’s success. The first one is their mindset. The most successful SDRs are capable of continuously finding opportunities in which MongoDB will fit companies' initiatives. The second is that they are willing to learn and improve consistently. They are curious, test new ideas, and continuously improve on their execution. As I continue to progress my career at MongoDB, I see myself as a Cloud Account Executive in my next role. I like the idea of helping companies embrace cloud technologies such as MongoDB Atlas. In today’s world, all modern applications are empowered with data. To make good use of data, all modern applications need to use cloud technologies that will operate independently. These technologies will help companies to boost development productivity, reduce complexity, and facilitate innovation. What makes MongoDB exciting and unique is to see how much the company is growing year over year and know that our work is contributing to this continuous success. MongoDB is full of incredibly talented and capable people, and I always learn something new from them. Interested in joining the Sales team at MongoDB? We have several open roles on our team and would love for you to transform your career with us!

November 10, 2021